Improved minimum error rate training in Moses

We describe an open-source implementation of minimum error rate training (MERT) for statistical machine translation (SMT). This was implemented within the Moses toolkit, al-though it is essentially standsalone, with the aim of replacing the existing implementation with a cleaner, more flexible design, in order to facilitate further research in weight optimi-sation. A description of the design is given, as well as experiments to compare performance with the previous implementation and to demonstrate extensibility